Y2K Interruption: Can the Doomsday Scenario Be Averted?

The management philosophy until recent years has been to replace the workers with computers, which are available 24 hours a day, need no benefits, no insurance and never complain. But as the year 2000 approached, along with it came the fear of the millennium bug, generally known as Y2K, and the computers threatened to strike!!!! Y2K, though an abbreviation of year 2000, generally refers to the computer glitches which are associated with the year 2000. Computer companies, in order to save memory and money, adopted a voluntary standard in the beginning of the computer era that all computers automatically convert any year designated by two numbers such as 99 into 1999 by adding the digits 19. This saved enormous amount of memory, and thus money, because large databases containing birth dates or other dates only needed to contain the last two digits such as 65 or 86. But it also created a built in flaw that could make the computers inoperable from January 2000. The problem is that most of these old computers are programmed to convert 00 (for the year 2000) into 1900 and not 2000. The trouble could therefore, arise when the systems had to deal with dates outside the 1900s. In 2000, for example a programme that calculates the age of a person born in 1965 will subtract 65 from 00 and get -65. The problem is most acute in mainframe systems, but that does not mean PCs, UNIX and other computing environments are trouble free. Any computer system that relies on date calculations must be tested because the Y2K or the millennium bug arises because of a potential for “date discontinuity” which occurs when the time expressed by a system, or any of its components, does not move in consonance with real time. Though attention has been focused on the potential problems linked with change from 1999 to 2000, date discontinuity may occur at other times in and around this period.

Is integrated private-clinic based early child development care effective? A clustered randomised trial in Pakistan

Background In Pakistan, high prevalence of delays in early child development (ECD) is associated with poverty and lack of mothers’ caregiving skills. GP clinics, the main sources of care in poor urban localities, lack quality ECD care delivery. A contextualised intervention was developed and tested to enable GPs to deliver clinic-based, tool-assisted ECD counselling of mothers on a quarterly basis. Aim To assess the effectiveness of delivering a contextualised ECD mother-counselling intervention. Design & setting Clustered randomised controlled trial, in poor urban localities of Pakistan. Locality clusters were allocated to intervention and control arm using simple randomisation. Method A total of 2327 mother–child pairs were recruited at 32 GP clinics, one from each cluster-locality; 16 GP clinics per arm. The clinic-based counselling intervention covering child stimulation, nutrition, and maternal mental health was delivered mainly by clinic assistants to mothers at ≤6 weeks, and 3, 6, and 9 months of child age. At 12 months of child age, each mother–child pair was assessed for the primary outcome, that is, delays in the five development domains (determined by Ages and Stages Questionnaire-3 [ASQ-3] score); and secondary outcomes, namely the prevalence of stunting and maternal depression (determined by Patient Health Questionnaire-9 [PHQ-9] score). The outcome assessors were blinded to the cluster–arm allocation. Outcome analyses were calculated on cluster-level. Results At 12 months, the number of children with delay in two or more development domains was significantly lower in the intervention arm (-0.17 [95% confidence interval {CI} = -0.26 to -0.09]; P<0.001) compared to the control arm. The difference in the prevalence of child stunting and maternal depression were also significant at -0.21% (95% CI = -0.30 to -0.13; P<0.001) and -0.23% (95% CI = -0.29 to -0.18; P = 0.000) respectively. Conclusion Contextualised ECD care, when delivered at GP clinics in poor urban localities, can effectively reduce the developmental delays during the first 12 months of the child's life

Delivering integrated child development care in Pakistan: protocol for a clustered randomised trial

Background: Early childhood developmental delay is associated with significant disadvantage in adult life. In Pakistan, high prevalence of developmental delay is associated with poverty, under-nutrition, and maternal depression. Aim: To assess the effectiveness of an early child development counselling intervention delivered at private GP clinics, in poor urban communities. Design & setting: A clustered randomised trial in Pakistan. Method: The intervention was developed following a period of formative research, and in consultation with local experts. A total of 2112 mother–child pairs will be recruited at 32 clinics, from within the locality (cluster); 16 clinics per arm. A primary care counselling intervention (promoting child development, nutrition, and maternal mental health) will be delivered at 6 weeks, 3, 6, and 9 months of the child’s age. Monitoring, assessment, and treatment will also be performed at quarterly visits in intervention clinics. Primary outcome is the developmental delay at 12 months (ASQ-3 scores). Secondary outcomes are stunting rate, and maternal depression (PHQ-9 score). In addition, a process evaluation and costing study will be conducted. Discussion: This trial will be the first to assess an early child development intervention, delivered in private GP clinics for poor urban communities in Pakistan. If found to be effective, this public–private model may offer a more sustainable, and feasible option for populations in poor urban settings, where private GP clinics are the most accessible provider of primary health care. There is scope for scale-up at provincial level, should the intervention be effective. Trial registration: The trial has been registered with the Current Controlled Trials ISRCTN48032200

Adapting an evidence-based intervention for autism spectrum disorder for scaling up in resource-constrained settings: the development of the PASS intervention in South Asia.

Evidence-based interventions for autism spectrum disorders evaluated in high-income countries typically require highly specialised manpower, which is a scarce resource in most low- and middle-income settings. This resource limitation results in most children not having access to evidence-based interventions. This paper reports on the systematic adaptation of an evidence-based intervention, the Preschool Autism Communication Therapy (PACT) evaluated in a large trial in the United Kingdom for delivery in a low-resource setting through the process of task-shifting. The adaptation process used the Medical Research Council framework for the development and adaptation of complex interventions, focusing on qualitative methods and case series and was conducted simultaneously in India and Pakistan. The original intervention delivered by speech and language therapists in a high-resource setting required adaptation in some aspects of its content and delivery to enhance contextual acceptability and to enable the intervention to be delivered by non-specialists. The resulting intervention, the Parent-mediated intervention for Autism Spectrum Disorder in South Asia (PASS), shares the core theoretical foundations of the original PACT but is adapted in several respects to enhance its acceptability, feasibility, and scalability in low-resource settings

MesoGraph: automatic profiling of mesothelioma subtypes from histological images

Mesothelioma is classified into three histological subtypes, epithelioid, sarcomatoid, and biphasic, according to the relative proportions of epithelioid and sarcomatoid tumor cells present. Current guidelines recommend that the sarcomatoid component of each mesothelioma is quantified, as a higher percentage of sarcomatoid pattern in biphasic mesothelioma shows poorer prognosis. In this work, we develop a dual-task graph neural network (GNN) architecture with ranking loss to learn a model capable of scoring regions of tissue down to cellular resolution. This allows quantitative profiling of a tumor sample according to the aggregate sarcomatoid association score. Tissue is represented by a cell graph with both cell-level morphological and regional features. We use an external multicentric test set from Mesobank, on which we demonstrate the predictive performance of our model. We additionally validate our model predictions through an analysis of the typical morphological features of cells according to their predicted score

Malignant Mesothelioma subtyping via sampling driven multiple instance prediction on tissue image and cell morphology data

Malignant Mesothelioma is a difficult to diagnose and highly lethal cancer usually associated with asbestos exposure. It can be broadly classified into three subtypes: Epithelioid, Sarcomatoid, and a hybrid Biphasic subtype in which significant components of both of the previous subtypes are present. Early diagnosis and identification of the subtype informs treatment and can help improve patient outcome. However, the subtyping of malignant mesothelioma, and specifically the recognition of transitional features from routine histology slides has a high level of inter-observer variability. In this work, we propose an end-to-end multiple instance learning (MIL) approach for malignant mesothelioma subtyping. This uses an adaptive instance-based sampling scheme for training deep convolutional neural networks on bags of image patches that allows learning on a wider range of relevant instances compared to max or top-N based MIL approaches. We also investigate augmenting the instance representation to include aggregate cellular morphology features from cell segmentation. The proposed MIL approach enables identification of malignant mesothelial subtypes of specific tissue regions. From this a continuous characterisation of a sample according to predominance of sarcomatoid vs epithelioid regions is possible, thus avoiding the arbitrary and highly subjective categorisation by currently used subtypes. Instance scoring also enables studying tumor heterogeneity and identifying patterns associated with different subtypes. We have evaluated the proposed method on a dataset of 234 tissue micro-array cores with an AUROC of 0.89±0.05 for this task. The dataset and developed methodology is available for the community at: https://github.com/measty/PINS

A review on the assessment of stress conditions for simultaneous production of microalgal lipids and carotenoids

Microalgal species are potential resource of both biofuels and high-value metabolites, and their production is growth dependent. Growth parameters can be screened for the selection of novel microalgal species that produce molecules of interest. In this context our review confirms that, autotrophic and heterotrophic organisms have demonstrated a dual potential, namely the ability to produce lipids as well as value-added products (particularly carotenoids) under influence of various physico-chemical stresses on microalgae. Some species of microalgae can synthesize, besides some pigments, very-long-chain polyunsaturated fatty acids (VL-PUFA,&gt;20C) such as docosahexaenoic acid and eicosapentaenoic acid, those have significant applications in food and health. Producing value-added by-products in addition to biofuels, fatty acid methyl esters (FAME), and lipids has the potential to improve microalgae-based biorefineries by employing either the autotrophic or the heterotrophic mode, which could be an offshoot of biotechnology. The review considers the potential of microalgae to produce a range of products and indicates future directions for developing suitable criteria for choosing novel isolates through bioprospecting large gene pool of microalga obtained from various habitats and climatic conditions